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Record W2488691038 · doi:10.1057/9781403973542_7

Monsters and Monstrosity

2003· book-chapter· en· W2488691038 on OpenAlexaboutno aff
Coral Ann Howells

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2003
Typebook-chapter
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsMonsterUncannySisterIdentity (music)HistoryArtLiteratureGenealogySubject (documents)BrotherWhite (mutation)Art historyPsychoanalysisSociologyAnthropologyAestheticsPsychology

Abstract

fetched live from OpenAlex

This heated argument between a brother and sister after the detective's visit following the murder of a neighbor and her lover goes to the heart of issues about identity and monstrosity that are explored in Kerri Sakamoto's The Electrical Field. In this discussion about contemporary Canadian literary traditions and the revision of national and cultural identities through fiction by racial minority writers, what might be the function of images of monstrosity in a novel written by a young Japanese Canadian woman in the late 1990s? Are they confined to the accusations hurled in a family quarrel? On the contrary, as I shall argue, the monster image has a wider resonance here, for this is a story that returns to a deliberately forgotten episode in Canada's recent past that casts its uncanny shadows over the present. This novel takes as its subject the psychological legacy of the internment of Japanese Canadians in World War II after Pearl Harbor, which was undergone by Sakamoto's parents and relatives and was first written about in fiction by Joy Kogawa in her novel Obasan (1981). Unlike Kogawa who was interned as a child, Sakamoto born fourteen years after the war looks back to an experience of which she saw only the aftermath.KeywordsYoung BrotherSocial InjusticeJapanese CulturePearl HarborInternment CampThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.626
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.205
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2003
Admission routes1
Has abstractyes

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